OpenML
Supervised Classification on Click_prediction_small

Supervised Classification on Click_prediction_small

Task 7295 Supervised Classification Click_prediction_small 39610 runs submitted
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6866, average_cost: 16.702, f_measure: 0.7581, kappa: 0.0124, kb_relative_information_score: -2507.6062, mean_absolute_error: 0.2629, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.7841, predictive_accuracy: 0.8318, prior_entropy: 0.6541, recall: 0.8318, relative_absolute_error: 0.9386, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3621, root_relative_squared_error: 0.9676, scimark_benchmark: 1853.454, total_cost: 667210, usercpu_time_millis: 459.648, usercpu_time_millis_testing: 11.078, usercpu_time_millis_training: 448.57,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6869, average_cost: 16.6246, f_measure: 0.7599, kappa: 0.0196, kb_relative_information_score: -2540.6343, mean_absolute_error: 0.2632, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.794, predictive_accuracy: 0.8324, prior_entropy: 0.6541, recall: 0.8324, relative_absolute_error: 0.9395, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.362, root_relative_squared_error: 0.9673, scimark_benchmark: 1843.1261, total_cost: 664120, usercpu_time_millis: 427.513, usercpu_time_millis_testing: 12.953, usercpu_time_millis_training: 414.56,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6919, average_cost: 16.3538, f_measure: 0.7656, kappa: 0.0435, kb_relative_information_score: -2728.994, mean_absolute_error: 0.2621, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.7983, predictive_accuracy: 0.8335, prior_entropy: 0.6541, recall: 0.8335, relative_absolute_error: 0.9355, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3605, root_relative_squared_error: 0.9632, scimark_benchmark: 1842.3188, total_cost: 653300, usercpu_time_millis: 454.279, usercpu_time_millis_testing: 15.621, usercpu_time_millis_training: 438.658,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6926, average_cost: 16.2394, f_measure: 0.7678, kappa: 0.0529, kb_relative_information_score: -2599.2195, mean_absolute_error: 0.2612, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.7962, predictive_accuracy: 0.8337, prior_entropy: 0.6541, recall: 0.8337, relative_absolute_error: 0.9323, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3603, root_relative_squared_error: 0.9626, scimark_benchmark: 1846.1774, total_cost: 648730, usercpu_time_millis: 439.713, usercpu_time_millis_testing: 10.12, usercpu_time_millis_training: 429.593,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.684, average_cost: 16.7217, f_measure: 0.7578, kappa: 0.011, kb_relative_information_score: -2445.6629, mean_absolute_error: 0.264, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.7983, predictive_accuracy: 0.8321, prior_entropy: 0.6541, recall: 0.8321, relative_absolute_error: 0.9425, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3625, root_relative_squared_error: 0.9685, scimark_benchmark: 1835.6541, total_cost: 668000, usercpu_time_millis: 427.747, usercpu_time_millis_testing: 12.376, usercpu_time_millis_training: 415.371,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.691, average_cost: 16.6554, f_measure: 0.7592, kappa: 0.0168, kb_relative_information_score: -2522.4887, mean_absolute_error: 0.2624, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.7925, predictive_accuracy: 0.8322, prior_entropy: 0.6541, recall: 0.8322, relative_absolute_error: 0.9366, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3614, root_relative_squared_error: 0.9656, scimark_benchmark: 1856.125, total_cost: 665350, usercpu_time_millis: 378.279, usercpu_time_millis_testing: 10.251, usercpu_time_millis_training: 368.028,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6923, average_cost: 16.8419, f_measure: 0.7551, kb_relative_information_score: -2297.2838, mean_absolute_error: 0.2653, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.6915, predictive_accuracy: 0.8316, prior_entropy: 0.6541, recall: 0.8316, relative_absolute_error: 0.9472, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3618, root_relative_squared_error: 0.9669, scimark_benchmark: 1847.3406, total_cost: 672800, usercpu_time_millis: 348.562, usercpu_time_millis_testing: 17.285, usercpu_time_millis_training: 331.277,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6887, average_cost: 16.2609, f_measure: 0.7673, kappa: 0.051, kb_relative_information_score: -3250.4669, mean_absolute_error: 0.2638, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.7956, predictive_accuracy: 0.8336, prior_entropy: 0.6541, recall: 0.8336, relative_absolute_error: 0.9416, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3609, root_relative_squared_error: 0.9643, scimark_benchmark: 1834.2399, total_cost: 649590, usercpu_time_millis: 339.959, usercpu_time_millis_testing: 13.979, usercpu_time_millis_training: 325.98,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6976, average_cost: 16.569, f_measure: 0.7612, kappa: 0.025, kb_relative_information_score: -2250.9408, mean_absolute_error: 0.2612, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.804, predictive_accuracy: 0.833, prior_entropy: 0.6541, recall: 0.833, relative_absolute_error: 0.9324, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.36, root_relative_squared_error: 0.9619, scimark_benchmark: 1854.0399, total_cost: 661900, usercpu_time_millis: 341.561, usercpu_time_millis_testing: 9.175, usercpu_time_millis_training: 332.386,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6978, average_cost: 16.2554, f_measure: 0.7676, kappa: 0.0519, kb_relative_information_score: -2188.9322, mean_absolute_error: 0.2596, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.7988, predictive_accuracy: 0.8339, prior_entropy: 0.6541, recall: 0.8339, relative_absolute_error: 0.9268, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3595, root_relative_squared_error: 0.9605, scimark_benchmark: 1848.321, total_cost: 649370, usercpu_time_millis: 309.514, usercpu_time_millis_testing: 6.029, usercpu_time_millis_training: 303.485,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6892, average_cost: 16.7696, f_measure: 0.7566, kappa: 0.0063, kb_relative_information_score: -2466.588, mean_absolute_error: 0.2635, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.7775, predictive_accuracy: 0.8316, prior_entropy: 0.6541, recall: 0.8316, relative_absolute_error: 0.9406, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3617, root_relative_squared_error: 0.9666, scimark_benchmark: 1847.3406, total_cost: 669910, usercpu_time_millis: 339.956, usercpu_time_millis_testing: 10.631, usercpu_time_millis_training: 329.325,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6924, average_cost: 16.0176, f_measure: 0.7722, kappa: 0.0716, kb_relative_information_score: -2566.9846, mean_absolute_error: 0.2588, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.7993, predictive_accuracy: 0.8347, prior_entropy: 0.6541, recall: 0.8347, relative_absolute_error: 0.9239, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3601, root_relative_squared_error: 0.9622, scimark_benchmark: 1830.668, total_cost: 639870, usercpu_time_millis: 308.202, usercpu_time_millis_testing: 5.124, usercpu_time_millis_training: 303.078,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6879, average_cost: 16.5948, f_measure: 0.7605, kappa: 0.0224, kb_relative_information_score: -2520.54, mean_absolute_error: 0.2629, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.7984, predictive_accuracy: 0.8326, prior_entropy: 0.6541, recall: 0.8326, relative_absolute_error: 0.9385, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3618, root_relative_squared_error: 0.9668, scimark_benchmark: 1853.9121, total_cost: 662930, usercpu_time_millis: 283.791, usercpu_time_millis_testing: 9.045, usercpu_time_millis_training: 274.746,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6905, average_cost: 16.8419, f_measure: 0.7551, kb_relative_information_score: -2319.6718, mean_absolute_error: 0.2661, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.6915, predictive_accuracy: 0.8316, prior_entropy: 0.6541, recall: 0.8316, relative_absolute_error: 0.9498, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3622, root_relative_squared_error: 0.968, scimark_benchmark: 1843.2259, total_cost: 672800, usercpu_time_millis: 317.078, usercpu_time_millis_testing: 16.103, usercpu_time_millis_training: 300.975,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7, average_cost: 16.4984, f_measure: 0.7627, kappa: 0.0315, kb_relative_information_score: -2052.7584, mean_absolute_error: 0.2617, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.8082, predictive_accuracy: 0.8335, prior_entropy: 0.6541, recall: 0.8335, relative_absolute_error: 0.9341, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3596, root_relative_squared_error: 0.9609, scimark_benchmark: 1835.621, total_cost: 659080, usercpu_time_millis: 273.036, usercpu_time_millis_testing: 10.091, usercpu_time_millis_training: 262.945,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6895, average_cost: 16.6246, f_measure: 0.7599, kappa: 0.0196, kb_relative_information_score: -2572.5054, mean_absolute_error: 0.2624, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.794, predictive_accuracy: 0.8324, prior_entropy: 0.6541, recall: 0.8324, relative_absolute_error: 0.9367, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3616, root_relative_squared_error: 0.9664, scimark_benchmark: 1852.0126, total_cost: 664120, usercpu_time_millis: 304.504, usercpu_time_millis_testing: 6.321, usercpu_time_millis_training: 298.183,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6692, average_cost: 16.7498, f_measure: 0.7572, kappa: 0.0085, kb_relative_information_score: -3141.0806, mean_absolute_error: 0.2674, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.7998, predictive_accuracy: 0.832, prior_entropy: 0.6541, recall: 0.832, relative_absolute_error: 0.9546, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3647, root_relative_squared_error: 0.9744, scimark_benchmark: 1848.388, total_cost: 669120, usercpu_time_millis: 272.833, usercpu_time_millis_testing: 10.339, usercpu_time_millis_training: 262.494,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6906, average_cost: 16.6108, f_measure: 0.7599, kappa: 0.02, kb_relative_information_score: -2548.057, mean_absolute_error: 0.2611, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.7793, predictive_accuracy: 0.8317, prior_entropy: 0.6541, recall: 0.8317, relative_absolute_error: 0.9323, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3614, root_relative_squared_error: 0.9656, scimark_benchmark: 1853.9121, total_cost: 663570, usercpu_time_millis: 234.111, usercpu_time_millis_testing: 2.663, usercpu_time_millis_training: 231.448,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6991, average_cost: 16.7125, f_measure: 0.7581, kappa: 0.0124, kb_relative_information_score: -1777.6048, mean_absolute_error: 0.2669, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.8276, predictive_accuracy: 0.8326, prior_entropy: 0.6541, recall: 0.8326, relative_absolute_error: 0.9526, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3614, root_relative_squared_error: 0.9658, scimark_benchmark: 1825.1897, total_cost: 667630, usercpu_time_millis: 210.572, usercpu_time_millis_testing: 12.123, usercpu_time_millis_training: 198.449,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6967, average_cost: 16.1888, f_measure: 0.7689, kappa: 0.0576, kb_relative_information_score: -2194.972, mean_absolute_error: 0.2591, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.8001, predictive_accuracy: 0.8343, prior_entropy: 0.6541, recall: 0.8343, relative_absolute_error: 0.9248, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3596, root_relative_squared_error: 0.961, scimark_benchmark: 1846.8212, total_cost: 646710, usercpu_time_millis: 248.145, usercpu_time_millis_testing: 3.804, usercpu_time_millis_training: 244.341,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6992, average_cost: 16.3518, f_measure: 0.7658, kappa: 0.0442, kb_relative_information_score: -2382.1158, mean_absolute_error: 0.2624, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.804, predictive_accuracy: 0.834, prior_entropy: 0.6541, recall: 0.834, relative_absolute_error: 0.9367, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3594, root_relative_squared_error: 0.9602, scimark_benchmark: 1829.632, total_cost: 653220, usercpu_time_millis: 244.144, usercpu_time_millis_testing: 13.955, usercpu_time_millis_training: 230.189,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6952, average_cost: 16.8056, f_measure: 0.756, kappa: 0.0035, kb_relative_information_score: -2074.1306, mean_absolute_error: 0.2685, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.8181, predictive_accuracy: 0.8318, prior_entropy: 0.6541, recall: 0.8318, relative_absolute_error: 0.9584, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3623, root_relative_squared_error: 0.9681, scimark_benchmark: 1825.1897, total_cost: 671350, usercpu_time_millis: 204.854, usercpu_time_millis_testing: 17.822, usercpu_time_millis_training: 187.032,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6541, average_cost: 16.7448, f_measure: 0.7573, kappa: 0.009, kb_relative_information_score: -3313.2825, mean_absolute_error: 0.2693, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.8018, predictive_accuracy: 0.8321, prior_entropy: 0.6541, recall: 0.8321, relative_absolute_error: 0.9615, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3663, root_relative_squared_error: 0.9787, scimark_benchmark: 1847.8629, total_cost: 668920, usercpu_time_millis: 183.754, usercpu_time_millis_testing: 7.742, usercpu_time_millis_training: 176.012,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6925, average_cost: 16.8419, f_measure: 0.7551, kb_relative_information_score: -1968.7805, mean_absolute_error: 0.2689, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.6915, predictive_accuracy: 0.8316, prior_entropy: 0.6541, recall: 0.8316, relative_absolute_error: 0.9599, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3633, root_relative_squared_error: 0.9707, scimark_benchmark: 1838.1471, total_cost: 672800, usercpu_time_millis: 218.224, usercpu_time_millis_testing: 15.112, usercpu_time_millis_training: 203.112,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.69, average_cost: 16.5448, f_measure: 0.7616, kappa: 0.0267, kb_relative_information_score: -2692.2907, mean_absolute_error: 0.2625, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.7953, predictive_accuracy: 0.8327, prior_entropy: 0.6541, recall: 0.8327, relative_absolute_error: 0.937, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3612, root_relative_squared_error: 0.9652, scimark_benchmark: 1833.1413, total_cost: 660930, usercpu_time_millis: 170.326, usercpu_time_millis_testing: 4.172, usercpu_time_millis_training: 166.154,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.669, average_cost: 16.8419, f_measure: 0.7551, kb_relative_information_score: -2863.1009, mean_absolute_error: 0.2702, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.6915, predictive_accuracy: 0.8316, prior_entropy: 0.6541, recall: 0.8316, relative_absolute_error: 0.9647, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3656, root_relative_squared_error: 0.9769, scimark_benchmark: 1845.7061, total_cost: 672800, usercpu_time_millis: 192.328, usercpu_time_millis_testing: 10.941, usercpu_time_millis_training: 181.387,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6852, average_cost: 16.8419, f_measure: 0.7551, kb_relative_information_score: -2384.6419, mean_absolute_error: 0.2686, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.6915, predictive_accuracy: 0.8316, prior_entropy: 0.6541, recall: 0.8316, relative_absolute_error: 0.9588, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3638, root_relative_squared_error: 0.972, scimark_benchmark: 1849.2344, total_cost: 672800, usercpu_time_millis: 163.408, usercpu_time_millis_testing: 10.595, usercpu_time_millis_training: 152.813,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6859, average_cost: 16.6381, f_measure: 0.7597, kappa: 0.0187, kb_relative_information_score: -2542.0878, mean_absolute_error: 0.2646, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.8026, predictive_accuracy: 0.8326, prior_entropy: 0.6541, recall: 0.8326, relative_absolute_error: 0.9445, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3622, root_relative_squared_error: 0.9679, scimark_benchmark: 1832.5979, total_cost: 664660, usercpu_time_millis: 159.749, usercpu_time_millis_testing: 10.188, usercpu_time_millis_training: 149.561,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6884, average_cost: 16.8419, f_measure: 0.7551, kb_relative_information_score: -2014.4712, mean_absolute_error: 0.27, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.6915, predictive_accuracy: 0.8316, prior_entropy: 0.6541, recall: 0.8316, relative_absolute_error: 0.9639, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3642, root_relative_squared_error: 0.9731, scimark_benchmark: 1854.6378, total_cost: 672800, usercpu_time_millis: 144.376, usercpu_time_millis_testing: 11.372, usercpu_time_millis_training: 133.004,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6759, average_cost: 16.7848, f_measure: 0.7562, kappa: 0.0045, kb_relative_information_score: -2745.0753, mean_absolute_error: 0.2655, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.7578, predictive_accuracy: 0.8312, prior_entropy: 0.6541, recall: 0.8312, relative_absolute_error: 0.9479, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3635, root_relative_squared_error: 0.9713, scimark_benchmark: 1803.9966, total_cost: 670520, usercpu_time_millis: 150.664, usercpu_time_millis_testing: 4.122, usercpu_time_millis_training: 146.542,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6703, average_cost: 16.8419, f_measure: 0.7551, kb_relative_information_score: -2819.5041, mean_absolute_error: 0.2697, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.6915, predictive_accuracy: 0.8316, prior_entropy: 0.6541, recall: 0.8316, relative_absolute_error: 0.9629, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3653, root_relative_squared_error: 0.9761, scimark_benchmark: 1840.2451, total_cost: 672800, usercpu_time_millis: 132.946, usercpu_time_millis_testing: 7.683, usercpu_time_millis_training: 125.263,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6746, average_cost: 16.8419, f_measure: 0.7551, kb_relative_information_score: -2662.8355, mean_absolute_error: 0.2707, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.6915, predictive_accuracy: 0.8316, prior_entropy: 0.6541, recall: 0.8316, relative_absolute_error: 0.9665, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3656, root_relative_squared_error: 0.9768, scimark_benchmark: 1836.7415, total_cost: 672800, usercpu_time_millis: 56.352, usercpu_time_millis_testing: 2.696, usercpu_time_millis_training: 53.656,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6623, average_cost: 16.8419, f_measure: 0.7551, kb_relative_information_score: -2483.8724, mean_absolute_error: 0.2736, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.6915, predictive_accuracy: 0.8316, prior_entropy: 0.6541, recall: 0.8316, relative_absolute_error: 0.9769, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3678, root_relative_squared_error: 0.9828, scimark_benchmark: 1839.8608, total_cost: 672800, usercpu_time_millis: 62.451, usercpu_time_millis_testing: 7.936, usercpu_time_millis_training: 54.515,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6879, average_cost: 16.8089, f_measure: 0.7559, kappa: 0.0031, kb_relative_information_score: -2438.6271, mean_absolute_error: 0.2672, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.7989, predictive_accuracy: 0.8317, prior_entropy: 0.6541, recall: 0.8317, relative_absolute_error: 0.9538, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3627, root_relative_squared_error: 0.9691, scimark_benchmark: 1850.9652, total_cost: 671480, usercpu_time_millis: 40.242, usercpu_time_millis_testing: 3.269, usercpu_time_millis_training: 36.973,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6898, average_cost: 16.5608, f_measure: 0.7613, kappa: 0.0256, kb_relative_information_score: -2625.7199, mean_absolute_error: 0.2625, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.8011, predictive_accuracy: 0.8329, prior_entropy: 0.6541, recall: 0.8329, relative_absolute_error: 0.9372, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3614, root_relative_squared_error: 0.9658, scimark_benchmark: 1849.3014, total_cost: 661570, usercpu_time_millis: 48.019, usercpu_time_millis_testing: 0.854, usercpu_time_millis_training: 47.165,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6839, average_cost: 15.9257, f_measure: 0.7737, kappa: 0.0785, kb_relative_information_score: -3488.2002, mean_absolute_error: 0.2618, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.7973, predictive_accuracy: 0.8347, prior_entropy: 0.6541, recall: 0.8347, relative_absolute_error: 0.9345, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3617, root_relative_squared_error: 0.9666, scimark_benchmark: 1789.3281, total_cost: 636200, usercpu_time_millis: 40.345, usercpu_time_millis_testing: 1.012, usercpu_time_millis_training: 39.333,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, average_cost: 16.8419, f_measure: 0.7551, kb_relative_information_score: 3.7762, mean_absolute_error: 0.2801, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.6915, predictive_accuracy: 0.8316, prior_entropy: 0.6541, recall: 0.8316, relative_absolute_error: 0.9999, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3742, root_relative_squared_error: 1, scimark_benchmark: 1857.6392, total_cost: 672800, usercpu_time_millis: 39.754, usercpu_time_millis_testing: 7.125, usercpu_time_millis_training: 32.629,

Metric:

Timeline

Plotting contribution timeline

Leaderboard

Rank Name Top Score Entries Highest rank

Note: The leaderboard ignores resubmissions of previous solutions, as well as parameter variations that do not improve performance.

Challenge

In supervised classification, you are given an input dataset in which instances are labeled with a certain class. The goal is to build a model that predicts the class for future unlabeled instances. The model is evaluated using a train-test procedure, e.g. cross-validation.

To make results by different users comparable, you are given the exact train-test folds to be used, and you need to return at least the predictions generated by your model for each of the test instances. OpenML will use these predictions to calculate a range of evaluation measures on the server.

You can also upload your own evaluation measures, provided that the code for doing so is available from the implementation used. For extremely large datasets, it may be infeasible to upload all predictions. In those cases, you need to compute and provide the evaluations yourself.

Optionally, you can upload the model trained on all the input data. There is no restriction on the file format, but please use a well-known format or PMML.

Given inputs

Expected outputs

evaluations A list of user-defined evaluations of the task as key-value pairs. KeyValue (optional)
model A file containing the model built on all the input data. File (optional)
predictions The desired output format Predictions (optional)

How to submit runs

Using your favorite machine learning environment

Download this task directly in your environment and automatically upload your results

OpenML bootcamp

From your own software

Use one of our APIs to download data from OpenML and upload your results

OpenML APIs